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Epidemiology > Confounding and Effect Modification > Flashcards

Confounding and Effect Modification Flashcards

1
Q

What is Confounding?

A

A 3rd variable (characteristic related to study subjects) that distort an association (RR/OR/HR) between exposure and outcome.

An alternative explanation of the association.

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2
Q

What is a second way to state confounding?

A

A mixing of effects; an association is distorted due to the 2 being mixed with another factor that is also associated with the outcome at the same time

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3
Q

What is a third way to state confounding?

A

A confusion of effects, where effect of exposure is distorted because the effect of an extraneous factor is mistaken for the effect of the exposure

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4
Q

What are the three requirements of confounders?

A
  1. Independently associated with the exposure
  2. Independently associated with the outcome
  3. Not directly in the casual-pathway linking exposure to outcome (independent)
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5
Q

What is the first step in testing for confounding?

A

Calculate crude measure of association (OR/RR) between exposure and outcome

AKA – unadjusted

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6
Q

What is the second step in testing for confounding?

A

Calculate outcome measure of association (OR/RR) between Exposure and Outcome for each individual strata of the 3rd variable (potential confounder)

Create a weighted-average of all strata
AKA – adjusted

NOTE: Authors must disclose this

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7
Q

What is the third step in testing for confounding?

A

Compare crude vs. adjusted RR/OR of measure of association between exposure and outcome

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8
Q

At what measure of difference between crude and adjusted estimates (RR/OR) is confounding present?

A

15%

10-20%

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9
Q

What are the two main impacts of confounders?

A
  1. Magnitude of Association

2. Direction of Association

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10
Q

Define Magnitude of Association

A

Association is either more or less extreme than the adjusted crude association

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11
Q

Define Direction of Association

A

May produce an association in an opposite direction

Towards or away from a null

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12
Q

What is the purpose of controlling for confounders?

A

To get a more precise (accurate), truer-estimate of the measure of association between exposure and outcome

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13
Q

What are the two main ways to control confounding?

A
  1. Study Design Stage

2. Analysis of Data Stage

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14
Q

In the Study Design Stage, what are the three ways to control confounding?

A
  1. Randomization (Simple or Stratified)
  2. Restriction
  3. Matching
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15
Q

In the Analysis of Data Stage, what are the two ways to control confounding?

A
  1. Stratification (w/ weighting)

2. Multivariative statistical analysis (Regression analyses)

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16
Q

What is Randomization?

A

Hopefully allocates an equal number of subjects with the known (and un-assessed) confounders into each intervention group

17
Q

What are the strengths of Randomization?

A
  • With sufficient sample size, will likely be successful in serving its purpose to make groups equal
  • Stratified version more precisely assures equal-ness
18
Q

What are the weaknesses of Randomization?

A
  • Sample size may not be large enough to control for all unknown or unassessed confounders
  • Process doesn’t guarantee successful, equal allocation between all intervention groups for all known and unknown confounders
  • Practical only for interventional studies
19
Q

What is Restriction?

A

Study participation is restricted to only subjects who do not fall within pre-specified category/ies of the confounder

20
Q

What are the strengths of Restriction?

A
  • Straight forward, convenient and inexpensive

- Does not negatively impact internal validity

21
Q

What are the weaknesses of Restriction?

A
  • Sufficiently narrow restriction criteria may negatively impact ability to enroll subjects (reduced sample size)
  • If restriction criteria is not sufficiently narrow it will allow the introduction of residual confounding effects
  • Eliminates researchers’ ability to evaluate varying levels of the factor being excluded
  • Can negatively impact external validity (generalizability)
22
Q

What is Matching?

A

Study subjects selected in matched-pairs related to the confounding variable, to equally distribute confounder among each study group

23
Q

What are the strengths of Matching?

A
  • Intuitive

- Some feel it gives greater analytic efficiency

24
Q

What are the weaknesses of Matching?

A
  • Difficult to accomplish, can be time consuming, and potentially expensive
  • Doesn’t control for any confounders other than those matched on – over-matching is possible and will mask blunt findings
25
Q

What is Stratification?

A

Descriptive & Statistical analysis of data evaluating association between Exposure and Outcome within the various strata (categories/levels) within the confounding variables

26
Q

What are the strengths of Stratification?

A
  • Intuitive, straight-forward and enhances understanding of data
27
Q

What are the weaknesses of Stratification?

A
  • Impractical for simultaneous control of multiple confounders, especially those with multiple strata within each variable being controlled
28
Q

What is Multivariate Analysis?

A

Statistical analysis of data by mathematically factoring out the effects of the confounding variables

29
Q

What are the strengths of Multivariate Analysis?

A
  • Can simultaneously control for multiple confounding variables
  • In statistical regression, OR’s can be obtained and interpreted
30
Q

What are the weaknesses of Multivariate Analysis?

A
  • Process requires individuals (researchers/readers) to clearly understand the data
  • Can be time consuming for researcher/biostatistician
31
Q

What is Effect Modification?

A

A 3rd variable, that when present, modifies the magnitude of effect of a true association by varying it within different strata of a 3rd variable

32
Q

What is Effect Modification also known as?

A

Interaction

33
Q

If an interaction is present, must the researcher report the measures of association for each strata individually?

A

Yes

34
Q

What is the first step in testing for Effect Modification?

A

Calculate crude measure of association between exposure and outcome (OR/RR)

35
Q

What is the second step in testing for Effect Modification?

A

Calculate strata-specific measures of association between exposure and outcome (OR/RR) for each strata of the 3rd variable

36
Q

What is the third step in testing for Effect Modification?

A

Compare each of the strata-specific measures of associations (OR/RR) between each other (while referencing adjusted measure of association)

37
Q

What is the difference in measure of association (RR/OR) between the lowest and highest strata if Effect Modification is present?

A

15%

Epidemiology (7 decks)

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